PM566 HW5

knitr::opts_chunk$set(include  = TRUE)
library(ggplot2)
library(tidyr)
library(data.table)
library(tidyverse)

## ── Attaching packages ─────────────────────────────────────── tidyverse 1.3.0 ──

## ✓ tibble  3.0.4     ✓ dplyr   1.0.2
## ✓ readr   1.4.0     ✓ stringr 1.4.0
## ✓ purrr   0.3.4     ✓ forcats 0.5.0

## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## x dplyr::between()   masks data.table::between()
## x dplyr::filter()    masks stats::filter()
## x dplyr::first()     masks data.table::first()
## x dplyr::lag()       masks stats::lag()
## x dplyr::last()      masks data.table::last()
## x purrr::transpose() masks data.table::transpose()

library(leaflet)
library(dplyr)
library(dtplyr)
library(plotly)

## 
## Attaching package: 'plotly'

## The following object is masked from 'package:ggplot2':
## 
##     last_plot

## The following object is masked from 'package:stats':
## 
##     filter

## The following object is masked from 'package:graphics':
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##     layout

library(knitr)
library(DT)
opts_chunk$set(
  warning = FALSE,
  message = FALSE,
  eval=TRUE,
  echo = TRUE,
  fig.width = 7, 
  fig.align = 'center',
  fig.asp = 0.618,
  out.width = "700px")

load("/Users/jiqingwu/Desktop/566 Introduction to Health Data Science/midterm/Arrest2010.rda")
load("/Users/jiqingwu/Desktop/566 Introduction to Health Data Science/midterm/Arrest2019.rda")

Arrest2010 %>% filter(Area.Name=="West LA") %>% 
plot_ly(x = ~Age, y = ~Arrest.Type, 
        color = ~PartOfDay, type = "scatter", mode = "markers", 
        size = ~SexCode, sizes = c(5, 10), marker = list(sizemode='diameter', opacity=0.5),
        hoverinfo = 'text',
        text = ~paste( paste("Age: ", Age, sep=""), 
                       paste("Arrest Type: ", Arrest.Type, sep=""), 
                       paste("Time: ", PartOfDay, sep=""), 
                       paste("Sex: ", Sex.Code, sep=""), 
                       sep = "<br>"))

g1 <- Arrest2010 %>% filter(Area.Name=="West LA") %>% 
  plot_ly(x = ~Age, type = "histogram", xbins = list(size = 1, end=30 ))
g2 <- Arrest2010 %>% filter(Area.Name=="West LA") %>% ggplot( aes(x=Age)) + geom_histogram(binwidth=1)
g2_plotly <- ggplotly(g2)
subplot(g1, g2_plotly)

ArrestTable <- Arrest2010 %>% filter(Area.Name=="West LA") %>% 
  select(Arrest.Date, Time, Arrest.Type, Age, Sex.Code)
datatable(ArrestTable)